Python Data Visualization Transcripts
Chapter: Visualization Concepts
Lecture: Working with data
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We've talked about data visualization quite a bit but I don't want to lose sight of
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the fact that a lot of data visualization should really be a part of working with
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your data. And I thought this quote from Mike Bostok really drove that home.
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I want to give one specific example of tidy data versus wide data to hammer this concept home. When we talk about tidy data,
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I mean data in the example that is one line has all the complete information. It's like a record in a database.
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So in this case for the amazon sales data we have the name of the book
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the author and the user rating and some other information by year we can transform that data into a wide data set using the pivot table function.
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So here we have the fiction and nonfiction reviews by year in the wide data format
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My point with all of this is that when we're doing data visualization,
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you need to be prepared and comfortable using tools like groupby, pivot table, or melt
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to get the data transformed in a way that is most effective for the visualization tool.